Supplementary Material for: Risk of Major Hemorrhage after Kidney Transplantation
Bibliographic record
Abstract
Background: Major hemorrhagic events are associated with significant morbidity and mortality. We examined the three-year cumulative incidence of hospitalization with major nontraumatic hemorrhage after kidney transplantation. Methods: We performed a retrospective cohort study using healthcare administrative data of all adult-incident kidney-only transplantation recipients in Ontario, Canada from 1994 to 2009. We calculated the three-year cumulative incidence, event rate, and incident rate ratio of hospitalization with major hemorrhage, its subtypes and those undergoing a hemorrhage-related procedure. Results were stratified by patient age and donor type and compared to a random and propensity-score matched sample from the general population. Results: Among 4,958 kidney transplant recipients, the three-year cumulative incidence of hospitalization with nontraumatic major hemorrhage was 3.5% (95% confidence interval [CI] 3.0-4.1%, 12.7 events per 1,000 patient-years) compared to 0.4% (95% CI 0.4-0.5%) in the general population (RR = 8.2, 95% CI 6.9-9.7). The crude risk of hemorrhage was 3-9-fold higher in all subtypes (upper/lower gastrointestinal, intra-cranial) and 15-fold higher for gastrointestinal endoscopic procedures compared to the random sample from the general population. After propensity score matching, the relative risk for major hemorrhage and its subtypes attenuated but remained elevated. The cumulative incidence of hemorrhage was higher for older individuals and those with a deceased donor kidney. Conclusion: Kidney transplantation recipients have a higher risk of hospitalization with hemorrhage compared to the general population, with about 1 in 30 recipients experiencing a major hemorrhage in the three years following transplant.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.808 | 0.204 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".